Combined heat and power and consumption optimization in a SCADA-based system

The operation of power systems in a Smart Grid (SG) context brings new opportunities to consumers as active players, in order to fully reach the SG advantages. In this context, concepts as smart homes or smart buildings are promising approaches to perform the optimization of the consumption, while reducing the electricity costs. This paper proposes an intelligent methodology to support the consumption optimization of an industrial consumer, which has a Combined Heat and Power (CHP) facility. A SCADA (Supervisory Control and Data Acquisition) system developed by the authors is used to support the implementation of the proposed methodology. An optimization algorithm implemented in the system in order to perform the determination of the optimal consumption and CHP levels in each instant, according to the Demand Response (DR) opportunities. The paper includes a case study with several scenarios of consumption and heat demand in the context of a DR event which specifies a maximum demand level for the consumer.

Power systems reliability calculation based on fuzzy data mining

This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.

Reactive power compensation by EPSO technique

This paper presents a methodology to address reactive power compensation using Evolutionary Particle Swarm Optimization (EPSO) technique programmed in the MATLAB environment. The main objective is to find the best operation point minimizing power losses with reactive power compensation, subjected to all operational constraints, namely full AC power flow equations, active and reactive power generation constraints. The methodology has been tested with the IEEE 14 bus test system demonstrating the ability and effectiveness of the proposed approach to handle the reactive power compensation problem.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Demand response in future power systems management – a conceptual framework and simulation tool

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Optimized near real-time remote device tracking and monitoring system

Os serviços baseados em localização vieram dar um novo alento à criatividade dos programadores de aplicações móveis. A vulgarização de dispositivos com capacidades de localização integradas deu origem ao desenvolvimento de aplicações que gerem e apresentam informação baseada na posição do utilizador. Desde então, o mercado móvel tem assistido ao aparecimento de novas categorias de aplicações que tiram proveito desta capacidade. Entre elas, destaca-se a monitorização remota de dispositivos, que tem vindo a assumir uma importância crescente, tanto no sector particular como no sector empresarial. Esta dissertação começa por apresentar o estado da arte sobre os diferentes sistemas de posicionamento, categorizados pela sua eficácia em ambientes internos ou externos, assim como diferentes protocolos de comunicação em tempo quase-real. É também feita uma análise ao estado actual do mercado móvel. Actualmente o mercado possui diferentes plataformas móveis com características únicas que as fazem rivalizar entre si, com vista a expandirem a sua quota de mercado. É por isso elaborado um breve estudo sobre os sistemas operativos móveis mais relevantes da actualidade. É igualmente feita uma abordagem mais profunda à arquitectura da plataforma móvel da Apple - o iOS – que serviu de base ao desenvolvimento de uma solução optimizada para localização e monitorização de dispositivos móveis. A monitorização implica uma utilização intensiva de recursos energéticos e de largura de banda que os dispositivos móveis da actualidade não estão aptos a suportar. Dado o grande consumo energético do GPS face à precária autonomia destes dispositivos, é apresentado um estudo em que se expõem soluções que permitem gerir de forma optimizada a utilização do GPS. O elevado custo dos planos de dados facultados pelas operadoras móveis é também considerado, pelo que são exploradas soluções que visam minimizar a utilização de largura de banda. Deste trabalho, nasce a aplicação EyeGotcha, que para além de permitir localizar outros utilizadores de dispositivos móveis de forma optimizada, permite também monitorizar as suas acções baseando-se num conjunto de regras pré-definidas. Estas acções são reportadas às entidades monitoras, de modo automatizado e sob a forma de alertas. Visionando-se a comercialização da aplicação, é portanto apresentado um modelo de negócio que permite obter receitas capazes de cobrirem os custos de manutenção de serviços, aos quais o funcionamento da aplicação móvel está subjugado.

Deteção e acompanhamento de movimento através de uma câmara de vídeo

A deteção e seguimento de pessoas tem uma grande variedade de aplicações em visão computacional. Embora tenha sido alvo de anos de investigação, continua a ser um tópico em aberto, e ainda hoje, um grande desafio a obtenção de uma abordagem que inclua simultaneamente exibilidade e precisão. O trabalho apresentado nesta dissertação desenvolve um caso de estudo sobre deteção e seguimento automático de faces humanas, em ambiente de sala de reuniões, concretizado num sistema flexível de baixo custo. O sistema proposto é baseado no sistema operativo GNU's Not Unix (GNU) linux, e é dividido em quatro etapas, a aquisição de vídeo, a deteção da face, o tracking e reorientação da posição da câmara. A aquisição consiste na captura de frames de vídeo das três câmaras Internet Protocol (IP) Sony SNC-RZ25P, instaladas na sala, através de uma rede Local Area Network (LAN) também ele já existente. Esta etapa fornece os frames de vídeo para processamento à detecção e tracking. A deteção usa o algoritmo proposto por Viola e Jones, para a identificação de objetos, baseando-se nas suas principais características, que permite efetuar a deteção de qualquer tipo de objeto (neste caso faces humanas) de uma forma genérica e em tempo real. As saídas da deteção, quando é identificado com sucesso uma face, são as coordenadas do posicionamento da face, no frame de vídeo. As coordenadas da face detetada são usadas pelo algoritmo de tracking, para a partir desse ponto seguir a face pelos frames de vídeo subsequentes. A etapa de tracking implementa o algoritmo Continuously Adaptive Mean-SHIFT (Camshift) que baseia o seu funcionamento na pesquisa num mapa de densidade de probabilidade, do seu valor máximo, através de iterações sucessivas. O retorno do algoritmo são as coordenadas da posição e orientação da face. Estas coordenadas permitem orientar o posicionamento da câmara de forma que a face esteja sempre o mais próximo possível do centro do campo de visão da câmara. Os resultados obtidos mostraram que o sistema de tracking proposto é capaz de reconhecer e seguir faces em movimento em sequências de frames de vídeo, mostrando adequabilidade para aplicação de monotorização em tempo real.

Engineering real-time applications with WorldFIP: tools and analysis

WorldFIP is standardised as European Norm EN 50170 - General Purpose Field Communication System. Field communication systems (fieldbuses) started to be widely used as the communication support for distributed computer-controlled systems (DCCS), and are being used in all sorts of process control and manufacturing applications within different types of industries. There are several advantages in using fieldbuses as a replacement of for the traditional point-to-point links between sensors/actuators and computer-based control systems. Indeed they concern economical ones (cable savings) but, importantly, fieldbuses allow an increased decentralisation and distribution of the processing power over the field. Typically DCCS have real-time requirements that must be fulfilled. By this, we mean that process data must be transferred between network computing nodes within a maximum admissible time span. WorldFIP has very interesting mechanisms to schedule data transfers. It explicit distinguishes to types of traffic: periodic and aperiodic. In this paper we describe how WorldFIP handles these two types of traffic, and more importantly, we provide a comprehensive analysis for guaranteeing the real-time requirements of both types of traffic. A major contribution is made in the analysis of worst-case response time of aperiodic transfer requests.

Tomographic imaging with a scanning laser ophtalmoscop

Retinal imaging with a confocal scaning laser Ophthalmoscope (cSLO) involves scanning a small laser beam over the retina and constructing an image from the reflected light. By applying the confocal principle, tomographic images can be produced by measuring a sequence of slices at different depths. However, the thickness of such slices, when compared with the retinal thickness, is too large to give useful 3D retinal images, if no processing is done. In this work, a prototype cSLO was modified in terms hardware and software to give the ability of doing the tomographic measurements with the maximum theoretical axial resolution possible. A model eye was built to test the performance of the system. A novel algorithm has been developed which fits a double Gaussian curve to the axial intensity profiles generated from a stack of images slices. The underlying assumption is that the laser light has mainly been reflected by two structures in the retina, the internal limiting membrane and the retinal pigment epithelium. From the fitted curve topographic images and novel thickness images of the retina can be generated. Deconvolution algorithms have also been developed to improve the axial resolution of the system, using a theoretically predicted cSLO point spread function. The technique was evaluated using measurements made on a model eye, four normal eyes and seven eyes containing retinal pathology. The reproducibility, accuracy and physiological measurements obtained, were compared with available published data, and showed good agreement. The difference in the measurements when using a double rather than a single Gaussian model was also analysed.

Device power management for real-time embedded systems

A large part of power dissipation in a system is generated by I/O devices. Increasingly these devices provide power saving mechanisms to inter alia enhance battery life. While I/O device scheduling has been studied in the past for realtime systems, the use of energy resources by these scheduling algorithms may be improved. These approaches are crafted considering a huge overhead of device transition. The technology enhancement has allowed the hardware vendors to reduce the device transition overhead and energy consumption. We propose an intra-task device scheduling algorithm for real time systems that allows to shut-down devices while ensuring the system schedulability. Our results show an energy gain of up to 90% in the best case when compared to the state-of-the-art.

Task assignment algorithms for two-type heterogeneous multiprocessors

Consider the problem of assigning real-time tasks on a heterogeneous multiprocessor platform comprising two different types of processors — such a platform is referred to as two-type platform. We present two linearithmic timecomplexity algorithms, SA and SA-P, each providing the follow- ing guarantee. For a given two-type platform and a given task set, if there exists a feasible task-to-processor-type assignment such that tasks can be scheduled to meet deadlines by allowing them to migrate only between processors of the same type, then (i) using SA, it is guaranteed to find such a feasible task-to- processor-type assignment where the same restriction on task migration applies but given a platform in which processors are 1+α/2 times faster and (ii) SA-P succeeds in finding 2 a feasible task-to-processor assignment where tasks are not allowed to migrate between processors but given a platform in which processors are 1+α/times faster, where 0<α≤1. The parameter α is a property of the task set — it is the maximum utilization of any task which is less than or equal to 1.

SPARTS: simulator for power aware and real-time systems

Real-time systems demand guaranteed and predictable run-time behaviour in order to ensure that no task has missed its deadline. Over the years we are witnessing an ever increasing demand for functionality enhancements in the embedded real-time systems. Along with the functionalities, the design itself grows more complex. Posed constraints, such as energy consumption, time, and space bounds, also require attention and proper handling. Additionally, efficient scheduling algorithms, as proven through analyses and simulations, often impose requirements that have significant run-time cost, specially in the context of multi-core systems. In order to further investigate the behaviour of such systems to quantify and compare these overheads involved, we have developed the SPARTS, a simulator of a generic embedded real- time device. The tasks in the simulator are described by externally visible parameters (e.g. minimum inter-arrival, sporadicity, WCET, BCET, etc.), rather than the code of the tasks. While our current implementation is primarily focused on our immediate needs in the area of power-aware scheduling, it is designed to be extensible to accommodate different task properties, scheduling algorithms and/or hardware models for the application in wide variety of simulations. The source code of the SPARTS is available for download at [1].

Comparing the schedulers and power saving strategies with SPARTS

We have developed SPARTS, a simulator of a generic embedded real-time device. It is designed to be extensible to accommodate different task properties, scheduling algorithms and/or hardware models for the wide variety of applications. SPARTS was developed to help the community investigate the behaviour of the real-time embedded systems and to quantify the associated constraints/overheads.

Cut-off point for WHOQOL-bref as a measure of quality of life of older adults

OBJECTIVE To propose a cut-off for the World Health Organization Quality of Life-Bref (WHOQOL-bref) as a predictor of quality of life in older adults. METHODS Cross-sectional study with 391 older adults registered in the Northwest Health District in Belo Horizonte, MG, Southeastern Brazil, between October 8, 2010 and May 23, 2011. The older adults’ quality of life was measured using the WHOQOL-bref. The analysis was rationalized by outlining two extreme and simultaneous groups according to perceived quality of life and satisfaction with health (quality of life good/satisfactory – good or very good self-reported quality of life and being satisfied or very satisfied with health – G5; and poor/very poor quality of life – poor or very poor self-reported quality of life and feeling dissatisfied or very dissatisfied with health – G6). A Receiver-Operating Characteristic curve (ROC) was created to assess the diagnostic ability of different cut-off points of the WHOQOL-bref. RESULTS ROC curve analysis indicated a critical value 60 as the optimal cut-off point for assessing perceived quality of life and satisfaction with health. The area under the curve was 0.758, with a sensitivity of 76.8% and specificity of 63.8% for a cut-off of ≥ 60 for overall quality of life (G5) and sensitivity 95.0% and specificity of 54.4% for a cut-off of < 60 for overall quality of life (G6). CONCLUSIONS Diagnostic interpretation of the ROC curve revealed that cut-off < 60 for overall quality of life obtained excellent sensitivity and negative predictive value for tracking older adults with probable worse quality of life and dissatisfied with health.